Senior Machine Learning Engineer - Personalization

Overview

Senior Machine Learning Engineer – Personalization

Location:

On‑site, 4 days in‑person at designated office location.

Our team designs and builds models that directly shape the user experience – powering personalization and engagement across our Disney Streaming suite, notably Disney+ and Hulu. We use a strong product mindset and focus on usability, ensuring every ML‑driven product enhances how users discover, interact, and enjoy our experiences. I am a member of this team and collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals.

As an Individual Contributor, you will lead recommendation and personalization algorithm research, development, and productionization for product areas, and coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. You will also help set the roadmap for algorithmic work.

• Algorithm Development and Maintenance:
  Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and explain methodologies to technical and non‑technical teams.
• Feature Engineering and Optimization:
  Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte‑scale datasets.
• Development Best Practices:
  Maintain existing and establish new algorithm development, testing, and deployment standards.
• Collaborate with product and business stakeholders:
  Identify and define new personalization opportunities and work with other data teams to improve data collection, experimentation, and analysis.

• Basic Qualifications:
• 5+ years of experience developing machine learning models, large‑scale data analysis, and/or data engineering.
• 5+ years of writing production‑level, scalable code (Python, SQL).
• 3+ years of experience developing algorithms for deployment to production systems.
• Deep understanding of modern machine learning (e.g., deep learning methods) and their mathematical underpinnings.
• Experience deploying and maintaining pipelines and engineering big‑data solutions using Databricks, S3, and Spark.
• Ability to gauge complexity and execute simple approaches for quick, effective solutions as appropriate.
• Strong written and verbal communication skills.
• Preferred Qualifications:
• MS or PhD in statistics, math, computer science, or related quantitative field.
• Production experience with developing content recommendation algorithms at scale.
• Experience building and deploying full‑stack ML pipelines (data extraction, mining, model training, feature development, testing, deployment).
• Familiar with metadata management, data lineage, and principles of data governance.
• Experience loading and querying cloud‑hosted databases.
• Experience with AWS and Databricks.
• Required
  
  Education:
  
  Bachelor’s Degree in Computer Science, Math, Statistics, or a related quantitative field.

Compensation includes an annual base salary in the range $148,700 – $199,400 (NY) or $141,900 – $190,300 (CA). The base pay is based on equity, geographic region, and experience. A bonus and/or long‑term incentive units may be provided, and you will receive a full range of medical, financial, and other benefits.